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Near-ML MIMO Detection Algorithm With LR-Aided Fixed-Complexity Tree Searching

delete2014-12-01
delete21
PRE
AI
H
Hyunsub Kim *
J
Jangyong Park
H
Hyukyeon Lee
J
Jaeseok Kim
DOI:10.1109/LCOMM.2014.2364217delete
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摘要

摘要

En 中文
In this paper, we propose a low-complexity multiple-input multiple-output (MIMO) detection algorithm with lattice-reduction-aided fixed-complexity tree searching which is motivated by the fixed-complexity sphere decoder (FSD). As the proposed scheme generates a fixed tree whose size is much smaller than that of the full expansion in the FSD, the computational complexity is reduced considerably. Nevertheless, the proposed scheme achieves a near-maximum-likelihood (ML) performance with a large number of transmit antennas and a high-order modulation. The experimental results demonstrate that the performance degradation of the proposed scheme is less than 0.5 dB at the bit error rate (BER) of 10(-5) for a 8 x 8 MIMO system with 256 QAM. Also, the proposed method reduces the complexity to about 1.23% of the corresponding FSD complexity.
Keyword:
MIMO
lattice reduction
tree searching
fixed-complexity sphere decoder
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期刊

IEEE Communications Letters 封面图
IEEE Communications Letters
IF:
4.4
论文数:
1.3W
被引数:
2.2W

机构

Y
Yonsei University
学者数:
4.8W
论文数: 4.6W
被引数: 5.2W
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